2 citations · 2 across the 7 of their papers we have counts for
10 papers
System-Self as a Data Structure: An Architectural Approach to Bounded Adaptation
Erwin Franz, Alhassan S. Yasin
Safety critical autonomous systems often adapt by adjusting controller parameters while keeping the underlying architecture fixed. This strategy breaks down when shifts in sensing,…
Proximal Policy Optimization with Evolutionary Mutations
Casimir Czworkowski, Stephen Hornish, Alhassan S. Yasin
Proximal Policy Optimization (PPO) is a widely used reinforcement learning algorithm known for its stability and sample efficiency, but it often suffers from premature convergence…
Transfer Learning from One Cancer to Another via Deep Learning Domain Adaptation
Justin Cheung, Samuel Savine, Calvin Nguyen +2
Supervised deep learning models often achieve excellent performance within their training distribution but struggle to generalize beyond it. In cancer histopathology, for example,…
Improving Artifact Robustness for CT Deep Learning Models Without Labeled Artifact Images via Domain Adaptation
Justin Cheung, Samuel Savine, Calvin Nguyen +2
If a CT scanner introduces a new artifact not present in the training labels, the model may misclassify the images. Although modern CT scanners include design features which mitiga…
Fusion Steering: Prompt-Specific Activation Control
Waldemar Chang, Alhassan Yasin
We present Fusion Steering, an activation steering methodology that improves factual accuracy in large language models (LLMs) for question-answering (QA) tasks. This approach intro…
Reinforcement Learning Framework for Quantitative Trading
Alhassan S. Yasin, Prabdeep S. Gill
The inherent volatility and dynamic fluctuations within the financial stock market underscore the necessity for investors to employ a comprehensive and reliable approach that integ…